CN114325740A - Speed measurement method and system applied to laser Doppler velocimeter - Google Patents
Speed measurement method and system applied to laser Doppler velocimeter Download PDFInfo
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Abstract
The invention discloses a speed measuring method and a system applied to a laser Doppler velocimeter, wherein the method comprises the following steps: collecting a motion signal of a measured object through a laser Doppler velocimeter, and setting parameters according to the motion signal; filtering and segmenting the motion signal according to the set parameters, converting the signal of each paragraph into a frequency domain through fast Fourier transform and performing spectrum analysis to obtain a frequency search range of the signal of each paragraph; performing wavelet transformation on the signals in the paragraphs through the set parameters and frequency search range, and extracting wavelet ridges to obtain instantaneous frequency estimation curve segments of each paragraph of signals; and splicing the instantaneous frequency estimation curve segments of each section, and reconstructing a time-frequency signal to obtain a speed-time curve of the measured object. The invention utilizes wavelet transformation to process signals, and combines fast Fourier transformation to effectively improve the time resolution and the data processing speed of the system.
Description
Technical Field
The invention relates to the field of speed and acceleration measurement, in particular to a speed measurement method and system applied to a laser Doppler velocimeter.
Background
The laser doppler measurement technique uses laser as an information carrier, irradiates a beam of laser on a moving target object, and obtains the moving speed information of the target object by detecting the frequency shift of scattered light relative to incident light, i.e. doppler shift, and using a data processing method. The laser Doppler velocity measurement technology has the advantages of non-contact measurement, no interference to target motion, high spatial resolution, high measurement precision, large measurement range and the like, and is widely applied to multiple industries such as military affairs, aviation, aerospace, machinery and the like.
The fourier transform algorithm is a frequency domain detection method commonly used at present, but frequency information on the whole time axis is obtained by fourier transform, the frequency information on a certain time period cannot be obtained, and the corresponding relation between transient time and frequency cannot be obtained. Therefore, the short-time fourier transform is usually adopted to improve the disadvantage, but the short-time fourier transform is fixed in window size, cannot change along with frequency, lacks of time localization property, is only suitable for a stationary signal with small frequency fluctuation, and has limitation on detection of a non-stationary signal with large frequency fluctuation.
Disclosure of Invention
The invention provides a speed measuring method and system applied to a laser Doppler velocimeter, aiming at the technical problem that the laser Doppler velocimeter adopts a single window length to have lower detection precision on non-stationary signal time frequency.
In a first aspect, an embodiment of the present application provides a speed measurement method applied to a laser doppler velocimeter, including:
a data acquisition step: acquiring a motion signal of a measured object through a laser Doppler velocimeter, and setting parameters according to the motion signal;
a data segmentation step: filtering and segmenting the motion signal according to the set parameters, and taking a starting paragraph as a current paragraph;
a fast Fourier transform step: converting the signal in the current paragraph into a frequency domain through fast Fourier transform and carrying out spectrum analysis to obtain a frequency search range of the signal in the current paragraph;
wavelet transformation: performing wavelet transformation on the signals in the current paragraph through the set parameters and the frequency search range, and extracting wavelet ridges to obtain instantaneous frequency estimation curve segments of the signals in the current paragraph;
speed-time curve obtaining step: judging whether the current paragraph is the last paragraph; if not, adding one to the number of the segments of the current paragraph, and returning to the fast Fourier transform step; and if so, splicing the instantaneous frequency estimation curve segments of the signals in each section, and reconstructing the time-frequency signals to obtain a speed-time curve of the measured object.
The speed measuring method, wherein the set parameters include: the speed detection range of the object to be detected, the data windowing length, the wavelet basis function and the step length of the wavelet transformation scale factor.
The speed measuring method, wherein the data segmenting step further comprises: and designing a band-pass filter according to the speed detection range of the object to be detected, and filtering the motion signal through the band-pass filter.
The speed measuring method, wherein the data segmenting step includes:
a step of obtaining the number of segments: calculating the number of the interception segments of the motion signal according to the total number of data points in the motion signal and the data windowing length;
a step of sectional treatment: and carrying out data segmentation on the filtered motion signal according to the number of the segments.
The velocity measurement method described above, wherein the fast fourier transform step includes:
an instantaneous frequency estimation value obtaining step: obtaining an instantaneous frequency estimation value of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum of the frequency spectrum in the frequency domain of the signal in the current paragraph;
frequency search range obtaining step: and determining the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimation value of the signal in the current paragraph.
The velocity measuring method described above, wherein the wavelet transforming step comprises:
scale factor search range obtaining step: obtaining the wavelet transform scale factor search range of the signals in the current paragraph according to the step length of the wavelet transform scale factor and the frequency search range of the signals in the current paragraph;
wavelet coefficient obtaining step: performing wavelet transformation on the signals in the current paragraph through the wavelet basis functions, the step size of the wavelet transformation scale factors and the scale factor search range of the wavelet transformation of the signals in the current paragraph to obtain wavelet coefficients;
wavelet ridge line extraction: and extracting a wavelet ridge line by adopting a modulus maximum value method according to the wavelet coefficient to obtain an instantaneous frequency estimation curve segment of the signal in the current paragraph.
The speed measuring method described above, wherein the speed-time curve obtaining step includes:
and (3) data splicing: splicing the instantaneous frequency estimation curve segments of each paragraph to obtain a signal instantaneous frequency spectrum estimation curve of a full time domain;
time-frequency signal reconstruction: and according to the signal instantaneous frequency spectrum estimation curve of the full time domain, a speed-time curve of the measured object is obtained through time-frequency signal reconstruction.
In a second aspect, an embodiment of the present application provides a speed measurement system applied to a laser doppler velocimeter, including:
a data acquisition unit: acquiring a motion signal of a measured object through a laser Doppler velocimeter, and setting parameters according to the motion signal;
a data segmentation unit: filtering and segmenting the motion signal according to the set parameters, and taking a starting paragraph as a current paragraph;
a fast Fourier transform unit: converting the signal in the current paragraph into a frequency domain through fast Fourier transform and carrying out spectrum analysis to obtain a frequency search range of the signal in the current paragraph;
a wavelet transform unit: performing wavelet transformation on the signals in the current paragraph through the set parameters and the frequency search range, and extracting wavelet ridges to obtain instantaneous frequency estimation curve segments of the signals in the current paragraph;
a speed-time curve obtaining unit: judging whether the current paragraph is the last paragraph; if not, adding one to the number of the segments of the current paragraph, and returning to the fast Fourier transform unit; and if so, splicing the instantaneous frequency estimation curve segments of the signals in each section, and reconstructing the time-frequency signals to obtain a speed-time curve of the measured object.
The velocity measurement system described above, wherein the fast fourier transform unit includes:
an instantaneous frequency estimate obtaining module: obtaining an instantaneous frequency estimation value of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum of the frequency spectrum in the frequency domain of the signal in the current paragraph;
a frequency search range acquisition module: and determining the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimation value of the signal in the current paragraph.
The above speed measurement system, wherein the wavelet transform unit comprises:
a scale factor search range obtaining module: obtaining the wavelet transform scale factor search range of the signals in the current paragraph according to the step length of the wavelet transform scale factor and the frequency search range of the signals in the current paragraph;
a wavelet coefficient obtaining module: performing wavelet transformation on the signals in the current paragraph through the wavelet basis functions, the step size of the wavelet transformation scale factors and the scale factor search range of the wavelet transformation of the signals in the current paragraph to obtain wavelet coefficients;
wavelet ridge extraction module: and extracting a wavelet ridge line by adopting a modulus maximum value method according to the wavelet coefficient to obtain an instantaneous frequency estimation curve segment of the signal in the current paragraph.
Compared with the prior art, the invention has the advantages and positive effects that:
1. the invention applies wavelet transformation to the laser Doppler velocimeter, breaks through the limitation of time-frequency analysis caused by window fixation when a conventional method is adopted, can adaptively adjust the size of the window according to the signal frequency, performs multi-resolution analysis, can focus on any details of signals for non-stationary signals with large fluctuation, better tracks the detail information of abrupt change positions of the signals, and has higher time resolution.
2. According to the invention, wavelet transformation and fast Fourier transformation are combined, and fast Fourier transformation is adopted to preprocess signals, so that the frequency change range of the signals in each time segment is determined, the search range of scale factors in the wavelet transformation is narrowed, the time resolution of non-stationary signal detection is improved, the operation amount of an algorithm is reduced, the data processing speed is accelerated, and the real-time performance of the system is improved.
Drawings
Fig. 1 is a schematic diagram illustrating a speed measurement method applied to a laser doppler velocimeter according to the present invention;
FIG. 2 is a schematic flow chart based on step S2 in FIG. 1 according to the present invention;
FIG. 3 is a schematic flow chart based on step S3 in FIG. 1 according to the present invention;
FIG. 4 is a schematic flowchart based on step S4 in FIG. 1 according to the present invention;
FIG. 5 is a schematic flow chart based on step S5 in FIG. 1 according to the present invention;
fig. 6 is a schematic flow chart of an embodiment of a velocity measurement method applied to a laser doppler velocimeter according to the present invention;
fig. 7 is a block diagram of a velocity measurement system applied to a laser doppler velocimeter according to the present invention;
wherein the reference numerals are:
11. a data acquisition unit; 12. a data segmentation unit; 13. a fast Fourier transform unit; 131. an instantaneous frequency estimation value obtaining module; 132. a frequency search range acquisition module; 14. a wavelet transform unit; 141. a scale factor search range obtaining module; 142. a wavelet coefficient obtaining module; 143. a wavelet ridge line extraction module; 15. a speed-time curve obtaining unit.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application.
It is obvious that the drawings in the following description are only examples or embodiments of the present application, and that it is also possible for a person skilled in the art to apply the present application to other similar contexts on the basis of these drawings without inventive effort. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of ordinary skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms referred to herein shall have the ordinary meaning as understood by those of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar words throughout this application are not to be construed as limiting in number, and may refer to the singular or the plural. The present application is directed to the use of the terms "including," "comprising," "having," and any variations thereof, which are intended to cover non-exclusive inclusions; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Reference to "connected," "coupled," and the like in this application is not intended to be limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as referred to herein means two or more. "and/or" describes an association relationship of associated objects, meaning that three relationships may exist, for example, "A and/or B" may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. Reference herein to the terms "first," "second," "third," and the like, are merely to distinguish similar objects and do not denote a particular ordering for the objects.
The present invention is described in detail with reference to the embodiments shown in the drawings, but it should be understood that these embodiments are not intended to limit the present invention, and those skilled in the art should understand that functional, methodological, or structural equivalents or substitutions made by these embodiments are within the scope of the present invention.
Before describing in detail the various embodiments of the present invention, the core inventive concepts of the present invention are summarized and described in detail by the following several embodiments.
The invention adopts the combination of fast Fourier transform and wavelet transform, carries out self-adaptive segmentation on signals acquired by a laser Doppler velocimeter, adopts fast Fourier transform preprocessing to preliminarily obtain the signal frequency change range in the segmentation so as to determine the search range and the step length of a scale factor of the wavelet transform, then carries out wavelet transform on the signals, extracts the ridge line of a wavelet coefficient, obtains the instantaneous frequency of a moving target object, and obtains the time-speed curve of the measured object through time-frequency signal reconstruction.
The first embodiment is as follows:
fig. 1 is a schematic step diagram of a velocity measurement method applied to a laser doppler velocimeter according to the present invention. As shown in fig. 1, this embodiment discloses a specific implementation of a speed measurement method (hereinafter referred to as "method") applied to a laser doppler velocimeter.
Wavelet Transform (WT) is a self-adaptive time-frequency analysis method, and its main characteristics are that it possesses good local characteristics in time and frequency, and can progressively make multi-scale refinement of signal by means of telescopic translation operation, and can focus on any details of signal, can make multi-resolution analysis, and is more effective for time-frequency analysis processing of non-stationary signal. However, the wavelet transform is relatively large in calculation amount, which is not favorable for the real-time performance of system signal processing and analysis. Therefore, the invention utilizes the method of combining wavelet transformation and fast Fourier transformation to reduce the operation amount of the algorithm and improve the real-time performance of the system while improving the time resolution of the detection of the non-stationary signal mutation moment.
Specifically, the method disclosed in this embodiment mainly includes the following steps:
step S1: acquiring a motion signal of a measured object through a laser Doppler velocimeter, and setting parameters according to the motion signal;
specifically, the set parameters include: the speed detection range of the object to be detected, the data windowing length, the wavelet basis function and the step length of the wavelet transformation scale factor.
Step S2: filtering and segmenting the motion signal according to the set parameters, and taking a starting paragraph as a current paragraph;
as shown in fig. 2, step S2 specifically includes the following contents:
step S21: designing a band-pass filter according to the speed detection range of the object to be detected, and filtering the motion signal through the band-pass filter;
step S22: calculating the number of the interception segments of the motion signal according to the total number of data points in the motion signal and the data windowing length;
step S23: and carrying out data segmentation on the filtered motion signal according to the number of the segments.
Step S3: converting the signal in the current paragraph into a frequency domain through fast Fourier transform and carrying out spectrum analysis to obtain a frequency search range of the signal in the current paragraph;
as shown in fig. 3, step S3 specifically includes the following contents:
step S31: obtaining an instantaneous frequency estimation value of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum of the frequency spectrum in the frequency domain of the signal in the current paragraph;
step S32: and determining the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimation value of the signal in the current paragraph.
Step S4: performing wavelet transformation on the signals in the current paragraph through the set parameters and the frequency search range, and extracting wavelet ridges to obtain instantaneous frequency estimation curve segments of the signals in the current paragraph;
as shown in fig. 4, step S4 specifically includes the following contents:
step S41: obtaining the wavelet transform scale factor search range of the signals in the current paragraph according to the step length of the wavelet transform scale factor and the frequency search range of the signals in the current paragraph;
step S42: performing wavelet transformation on the signals in the current paragraph through the wavelet basis functions, the step size of the wavelet transformation scale factors and the scale factor search range of the wavelet transformation of the signals in the current paragraph to obtain wavelet coefficients;
step S43: and extracting a wavelet ridge line by adopting a modulus maximum value method according to the wavelet coefficient to obtain an instantaneous frequency estimation curve segment of the signal in the current paragraph.
Step S5: judging whether the current paragraph is the last paragraph; if not, adding one to the segment number of the current paragraph, and returning to the step S3; and if so, splicing the instantaneous frequency estimation curve segments of the signals in each section, and reconstructing the time-frequency signals to obtain a speed-time curve of the measured object.
As shown in fig. 5, step S5 specifically includes the following contents:
step S51: splicing the instantaneous frequency estimation curve segments of each paragraph to obtain a signal instantaneous frequency spectrum estimation curve of a full time domain;
step S52: and according to the signal instantaneous frequency spectrum estimation curve of the full time domain, a speed-time curve of the measured object is obtained through time-frequency signal reconstruction.
Please refer to fig. 6. Fig. 6 is a schematic flow chart of an embodiment of a velocity measurement method applied to a laser doppler velocimeter, which is provided by the present invention, and the application flow of the method is specifically described as follows with reference to fig. 6:
the first step is as follows: the laser Doppler velocimeter acquires data to obtain a motion signal of a measured object;
the second step is that: setting parameters according to the collected motion signals: setting the speed detection range of a detected object, the data windowing length, the wavelet basis function and the step length of the wavelet transformation scale factor;
the third step: designing a band-pass filter according to the speed detection range in the second step;
the fourth step: filtering the motion signal acquired by the laser Doppler velocimeter by a band-pass filter in the third step to remove noise;
the fifth step: calculating the number of data interception segments according to the total number of data points acquired by the laser Doppler velocimeter and the data windowing length set in the second step;
and a sixth step: carrying out data segmentation on the motion signal subjected to filtering processing obtained in the fourth step according to the data truncation number;
the seventh step: initializing the parameter value of the current paragraph to be 1;
eighth step: converting the signals in the current paragraph into a frequency domain by adopting fast Fourier transform, and performing spectrum analysis;
the ninth step: obtaining instantaneous frequency estimation of the current paragraph signal by solving the frequency corresponding to the modulus maximum of the frequency spectrum in the frequency domain;
the tenth step: determining the frequency search range of the current paragraph signal according to the obtained instantaneous frequency estimation value of the current paragraph signal;
the eleventh step: calculating to obtain the searching range of the scale factor of the wavelet transform of the current paragraph according to the step length of the wavelet transform scale factor set in the second step and the frequency searching range of the current paragraph signal determined in the tenth step;
the twelfth step: performing wavelet transformation on the signals in the current paragraph according to the wavelet basis functions set in the first step, the step size of the wavelet transformation scale factors and the scale factor search range of the continuous wavelet transformation of the current paragraph obtained in the tenth step;
the thirteenth step: extracting a wavelet ridge line by adopting a modulus maximum value method, and obtaining an instantaneous frequency estimation curve segment of the current paragraph signal through the relation between a scale factor and an instantaneous frequency of a wavelet;
the fourteenth step is that: it is determined whether the current paragraph is the last paragraph. If not, adding one to the parameter value of the current paragraph, and jumping to the eighth step. If yes, ending the circulation and jumping to the fifteenth step;
the fifteenth step: and splicing the instantaneous frequency estimation curve segments obtained from each section to obtain a signal instantaneous frequency spectrum estimation curve of the full time domain.
Sixteenth, step: and (5) reconstructing the time-frequency signal, and calculating to obtain a speed-time curve of the measured object.
An embodiment of the velocity measurement method applied to the laser doppler velocimeter according to the present invention is further described in detail with reference to specific formulas.
The first step is as follows: the laser Doppler velocimeter acquires data to obtain a motion signal S (T) of a measured object, wherein,
Fssampling frequency, N, for Doppler velocimeterssThe total number of data collected by the Doppler velocimeter is counted.
The second step is that: setting the speed detection range of the object to be detected: vminAnd Vmax(ii) a Setting measurement parameters: wavelet basis function psia(t), the step length df of the wavelet transformation scale factor a and the data windowing length wlen;
the third step: designing a band-pass filter according to the speed detection range in the second step, wherein the passband cut-off frequency of the band-pass filter is as follows:
the stopband cutoff frequency of the bandpass filter is:
wherein lambda is the laser wavelength adopted by the Doppler velocimeter;
the fourth step: filtering the motion signal acquired by the laser Doppler velocimeter by using the band-pass filter in the third step to remove noise;
the fifth step: according to the total number N of data collected by the laser Doppler velocimetersAnd the data windowing length wlen set in the first step, calculating the number of sections of the motion signal to be intercepted
And a sixth step: the motion signal obtained in the fourth step after filtering processing is intercepted into N sections, and each section of signal Si(ti) Is wlen, where i ═ 1,2, …, N,
the seventh step: initializing a current paragraph parameter value i to be 1;
eighth step: converting the signal of the current paragraph into the frequency domain S using a fast Fourier transformi(ω)＝FFT(Si(ti) Performing spectral analysis;
the ninth step: obtaining an instantaneous frequency estimate of the signal in the current segment by solving for frequencies corresponding to the modulo maxima of the frequency spectrum in the frequency domain
The tenth step: determining the frequency search range [ f ] of the current paragraph signal according to the obtained instantaneous frequency estimation value of each paragraphmin(i),fmax(i)],i＝1,2,…,N。
The eleventh step: calculating to obtain the searching range of the scale factor in the continuous wavelet transform of the current paragraph signal according to the step length of the wavelet transform scale factor set in the first step and the frequency searching range obtained in the tenth step
The twelfth step: using the wavelet basis function ψ set in the first stepa(t) step size df of wavelet transform scale factor a and scale factor search range a of wavelet transform of current paragraph obtained in the tenth stepiWavelet transform is performed on the signal in the current paragraph to obtain wavelet coefficients
The thirteenth step: extracting wavelet ridge line by adopting a modulus maximum value method to obtain instantaneous frequency estimation curve segment of the current paragraph signal
The fourteenth step is that: judging whether the current paragraph is the last paragraph, namely judging whether the parameter value of the current paragraph is larger than N, if not, changing the parameter value i of the current paragraph to i +1, and jumping to the eighth step; if yes, ending the circulation and jumping to the fifteenth step;
the fifteenth step: the instantaneous frequency estimation curve segment obtained in the tenth step
The data splicing is carried out to obtain
Wherein
Sixteenth, step: through the reconstruction of time-frequency signals, a speed-time curve is obtained through calculation
The invention utilizes the time-frequency characteristics of wavelet transform multiresolution analysis to process the signals, thereby improving the time precision of object motion speed detection; and wavelet transformation and fast Fourier transformation are combined, and self-adaptive adjustment is carried out on a frequency search space, so that the data processing speed is effectively increased, and the real-time performance of the system is improved.
Example two:
in combination with the speed measurement method applied to the laser doppler velocimeter disclosed in the first embodiment, this embodiment discloses a specific implementation example of a speed measurement system (hereinafter referred to as "system") applied to the laser doppler velocimeter.
Referring to fig. 7, the system includes:
the data acquisition unit 11: acquiring a motion signal of a measured object through a laser Doppler velocimeter, and setting parameters according to the motion signal;
the data segmentation unit 12: filtering and segmenting the motion signal according to the set parameters, and taking a starting paragraph as a current paragraph;
fast fourier transform section 13: converting the signal in the current paragraph into a frequency domain through fast Fourier transform and carrying out spectrum analysis to obtain a frequency search range of the signal in the current paragraph;
specifically, the fast fourier transform section 13 includes:
instantaneous frequency estimate acquisition module 131: obtaining an instantaneous frequency estimation value of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum of the frequency spectrum in the frequency domain of the signal in the current paragraph;
the frequency search range obtaining module 132: and determining the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimation value of the signal in the current paragraph.
The wavelet transform unit 14: performing wavelet transformation on the signals in the current paragraph through the set parameters and the frequency search range, and extracting wavelet ridges to obtain instantaneous frequency estimation curve segments of the signals in the current paragraph;
specifically, the wavelet transform unit 14 described above includes:
the scale factor search range obtaining module 141: obtaining the wavelet transform scale factor search range of the signals in the current paragraph according to the step length of the wavelet transform scale factor and the frequency search range of the signals in the current paragraph;
wavelet coefficient obtaining module 142: performing wavelet transformation on the signals in the current paragraph through the wavelet basis functions, the step size of the wavelet transformation scale factors and the scale factor search range of the wavelet transformation of the signals in the current paragraph to obtain wavelet coefficients;
wavelet ridge extraction module 143: and extracting a wavelet ridge line by adopting a modulus maximum value method according to the wavelet coefficient to obtain an instantaneous frequency estimation curve segment of the signal in the current paragraph.
The speed-time curve obtaining unit 15: judging whether the current paragraph is the last paragraph; if not, adding one to the number of the segments of the current paragraph, and returning to the fast Fourier transform unit 13; and if so, splicing the instantaneous frequency estimation curve segments of the signals in each section, and reconstructing the time-frequency signals to obtain a speed-time curve of the measured object.
For a speed measurement system applied to a laser doppler velocimeter disclosed in this embodiment and a technical solution of the same parts in the speed measurement method applied to the laser doppler velocimeter disclosed in the first embodiment, please refer to the description of the first embodiment, which is not repeated herein.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A speed measuring method applied to a laser Doppler velocimeter is characterized by comprising the following steps:
a data acquisition step: acquiring a motion signal of a measured object through a laser Doppler velocimeter, and setting parameters according to the motion signal;
a data segmentation step: filtering and segmenting the motion signal according to the set parameters, and taking a starting paragraph as a current paragraph;
a fast Fourier transform step: converting the signal in the current paragraph into a frequency domain through fast Fourier transform and carrying out spectrum analysis to obtain a frequency search range of the signal in the current paragraph;
wavelet transformation: performing wavelet transformation on the signals in the current paragraph through the set parameters and the frequency search range, and extracting wavelet ridges to obtain instantaneous frequency estimation curve segments of the signals in the current paragraph;
speed-time curve obtaining step: judging whether the current paragraph is the last paragraph; if not, adding one to the number of the segments of the current paragraph, and returning to the fast Fourier transform step; and if so, splicing the instantaneous frequency estimation curve segments of the signals in each section, and reconstructing the time-frequency signals to obtain a speed-time curve of the measured object.
2. The speed measurement method according to claim 1, wherein the set parameter includes: the speed detection range of the object to be detected, the data windowing length, the wavelet basis function and the step length of the wavelet transformation scale factor.
3. The speed measurement method of claim 2, wherein the data segmenting step further comprises: and designing a band-pass filter according to the speed detection range of the object to be detected, and filtering the motion signal through the band-pass filter.
4. The speed measurement method of claim 3, wherein the data segmenting step comprises:
a step of obtaining the number of segments: calculating the number of the interception segments of the motion signal according to the total number of data points in the motion signal and the data windowing length;
a step of sectional treatment: and carrying out data segmentation on the filtered motion signal according to the number of the segments.
5. The velocity measurement method according to claim 4, wherein the fast Fourier transforming step comprises:
an instantaneous frequency estimation value obtaining step: obtaining an instantaneous frequency estimation value of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum of the frequency spectrum in the frequency domain of the signal in the current paragraph;
frequency search range obtaining step: and determining the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimation value of the signal in the current paragraph.
6. The velocity measurement method according to claim 5, wherein the wavelet transforming step comprises:
scale factor search range obtaining step: obtaining the wavelet transform scale factor search range of the signals in the current paragraph according to the step length of the wavelet transform scale factor and the frequency search range of the signals in the current paragraph;
wavelet coefficient obtaining step: performing wavelet transformation on the signals in the current paragraph through the wavelet basis functions, the step size of the wavelet transformation scale factors and the scale factor search range of the wavelet transformation of the signals in the current paragraph to obtain wavelet coefficients;
wavelet ridge line extraction: and extracting a wavelet ridge line by adopting a modulus maximum value method according to the wavelet coefficient to obtain an instantaneous frequency estimation curve segment of the signal in the current paragraph.
7. The speed measurement method according to claim 6, wherein the speed-time curve obtaining step includes:
and (3) data splicing: splicing the instantaneous frequency estimation curve segments of each paragraph to obtain a signal instantaneous frequency spectrum estimation curve of a full time domain;
time-frequency signal reconstruction: and according to the signal instantaneous frequency spectrum estimation curve of the full time domain, a speed-time curve of the measured object is obtained through time-frequency signal reconstruction.
8. A velocity measurement system applied to a laser Doppler velocimeter is characterized by comprising:
a data acquisition unit: acquiring a motion signal of a measured object through a laser Doppler velocimeter, and setting parameters according to the motion signal;
a data segmentation unit: filtering and segmenting the motion signal according to the set parameters, and taking a starting paragraph as a current paragraph;
a fast Fourier transform unit: converting the signal in the current paragraph into a frequency domain through fast Fourier transform and carrying out spectrum analysis to obtain a frequency search range of the signal in the current paragraph;
a wavelet transform unit: performing wavelet transformation on the signals in the current paragraph through the set parameters and the frequency search range, and extracting wavelet ridges to obtain instantaneous frequency estimation curve segments of the signals in the current paragraph;
a speed-time curve obtaining unit: judging whether the current paragraph is the last paragraph; if not, adding one to the number of the segments of the current paragraph, and returning to the fast Fourier transform unit; and if so, splicing the instantaneous frequency estimation curve segments of the signals in each section, and reconstructing the time-frequency signals to obtain a speed-time curve of the measured object.
9. The velocity measurement system of claim 8, wherein the fast fourier transform unit comprises:
an instantaneous frequency estimate obtaining module: obtaining an instantaneous frequency estimation value of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum of the frequency spectrum in the frequency domain of the signal in the current paragraph;
a frequency search range acquisition module: and determining the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimation value of the signal in the current paragraph.
10. The velocity measurement system according to claim 9, wherein the wavelet transform unit comprises:
a scale factor search range obtaining module: obtaining the wavelet transform scale factor search range of the signals in the current paragraph according to the step length of the wavelet transform scale factor and the frequency search range of the signals in the current paragraph;
a wavelet coefficient obtaining module: performing wavelet transformation on the signals in the current paragraph through the wavelet basis functions, the step size of the wavelet transformation scale factors and the scale factor search range of the wavelet transformation of the signals in the current paragraph to obtain wavelet coefficients;
wavelet ridge extraction module: and extracting a wavelet ridge line by adopting a modulus maximum value method according to the wavelet coefficient to obtain an instantaneous frequency estimation curve segment of the signal in the current paragraph.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115126963A (en) * | 2022-06-21 | 2022-09-30 | 安徽省特种设备检测院 | Detection signal processing method and system of internal detector |
| CN117168604A (en) * | 2023-09-04 | 2023-12-05 | 中冶建筑研究总院有限公司 | Doppler vectorization test method for structural vibration frequency |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115126963A (en) * | 2022-06-21 | 2022-09-30 | 安徽省特种设备检测院 | Detection signal processing method and system of internal detector |
| CN115126963B (en) * | 2022-06-21 | 2022-12-30 | 安徽省特种设备检测院 | Detection signal processing method and system of internal detector |
| CN117168604A (en) * | 2023-09-04 | 2023-12-05 | 中冶建筑研究总院有限公司 | Doppler vectorization test method for structural vibration frequency |
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